Following previous works [1]}, [2]}, [3]}, we evaluate our model and all baselines on two widely used datasets: NYT [4]} and WebNLG [5]}.
The former is generated for distant supervised relation extraction.
The latter is originally created for natural language generation (NLG).
Both NYT and WebNLG have two versions: one version only annotates the last word of entities, and the other version annotates the whole span of entities.
We denote the first version datasets as NYT\(^*\)  and WebNLG\(^*\) , and the second version as NYT and WebNLG.
To further study the capability of the proposed OneRel in handling complex scenarios, we split the test set by overlapping patterns and triple number.
Detailed statistics of the two datasets are described in Table 1.
